package redblacktree;

import map.FileOperation;

import java.util.ArrayList;

/**
 * 红黑树，与2-3树等价
 * 性质:
 * （1）每个节点或者是黑色，或者是红色。
 * （2）根节点是黑色。
 * （3）每个叶子节点（NIL）是黑色。 [注意：这里叶子节点，是指为空(NIL或NULL)的叶子节点！]
 * （4）如果一个节点是红色的，则它的子节点必须是黑色的。
 * （5）从一个节点到该节点的子孙节点的所有路径上包含相同数目的黑节点。
 * @param <K>
 * @param <V>
 */
public class RBTree<K extends Comparable<K>, V> {
    private static final boolean RED = true;
    private static final boolean BLACK = false;

    private class Node {
        public K key;
        public V value;
        public Node left, right;
        public boolean color;

        public Node(K key, V value){
            this.key = key;
            this.value = value;
            left = null;
            right = null;
            color = RED;
        }
    }

    private Node root;
    private int size;

    public RBTree(){
        root = null;
        size = 0;
    }

    private boolean isRed(Node node){
        if (node == null){
            return BLACK;
        }
        return node.color;
    }

    //   node                     x
    //  /   \     左旋转         /  \
    // T1   x   --------->   node   T3
    //     / \              /   \
    //    T2 T3            T1   T2
    private Node leftRotate(Node node){
        Node x = node.right;

        //左旋转
        node.right = x.left;
        x.left = node;

        x.color = node.color;
        node.color = RED;

        return x;
    }

    //     node                   x
    //    /   \     右旋转       /  \
    //   x    T2   ------->   y   node
    //  / \                       /  \
    // y  T1                     T1  T2
    private Node rightRotate(Node node){
        Node x = node.left;
        // 右旋转
        node.left = x.right;
        x.right = node;

        x.color = node.color;
        node.color = RED;

        return x;

    }

    private void flipColors(Node node){
        node.color = RED;
        node.left.color = BLACK;
        node.right.color = BLACK;
    }

    // 添加元素
    public void add(K key, V value) {
        root = add(root, key, value);
        root.color = BLACK; // 最终根节点为黑色节点
    }
    //向以node为根的二分搜索树中插入元素(key, value),递归算法
    //返回插入新节点后二分搜索树的根
    private Node add(Node node, K key, V value) {
        if (node == null){
            size++;
            return new Node(key, value);
        }
        if (key.compareTo(node.key) < 0){
            node.left = add(node.left, key, value);
        } else if (key.compareTo(node.key) > 0){
            node.right = add(node.right, key, value);
        } else {
            node.value = value;
        }

        if (isRed(node.right) && !isRed(node.left)){
            node = leftRotate(node);
        }
        if (isRed(node.left) && isRed(node.left.left)){
            node = rightRotate(node);
        }
        if (isRed(node.left) && isRed(node.right)){
            flipColors(node);
        }
        return node;
    }

    //返回以node为根节点的二分搜索树中,key所在的节点
    private Node getNode(Node node, K key){
        if(node == null){
            return null;
        }
        if(key.compareTo(node.key) == 0){
            return node;
        } else if(key.compareTo(node.key) < 0){
            return  getNode(node.left, key);
        } else {
            return getNode(node.right, key);
        }
    }


    public boolean contains(K key) {
        return getNode(root, key) != null;
    }

    public V get(K key) {
        Node node = getNode(root, key);
        return node == null? null : node.value;
    }

    public void set(K key, V newValue) {
        Node node = getNode(root, key);
        if(node == null){
            throw new IllegalArgumentException(key + " doesn't exist!");
        }
        node.value = newValue;
    }
    // 返回以node为根的二分搜索树的最小值所在的节点
    private Node minimum(Node node){
        if(node.left == null){
            return node;
        }
        return minimum(node.left);
    }
    //删除掉以node为根的二分搜索树中的最小节点
    // 返回删除节点后新的二分搜索树的根
    private Node removeMin(Node node) {
        if(node.left == null){
            Node rightNode = node.right;
            node.right = null;
            size--;
            return rightNode;
        }
        node.left = removeMin(node.left);
        return node;
    }
    public V remove(K key) {
        Node node = getNode(root, key);
        if(node != null){
            root = remove(root, key);
            return node.value;
        }
        return null;
    }
    //删除以node为根的二分搜索树中键为key的节点 递归算法
    // 返回删除节点后新的二分搜索树的根
    private Node remove(Node node, K key) {
        if(node == null){
            return null;
        }
        if(key.compareTo(node.key) < 0){
            node.left = remove(node.left, key);
            return node;
        } else if(key.compareTo(node.key) > 0){
            node.right = remove(node.right, key);
            return node;
        } else {
            //待删除的节点左子树为空的情况
            if(node.left == null){
                Node rightNode = node.right;
                node.right = null;
                size --;
                return rightNode;
            }
            //待删除的节点右子树为空的情况
            if(node.right == null){
                Node leftNode = node.left;
                node.left = null;
                size--;
                return leftNode;
            }

            //待删除的节点左右子树都不为空的情况
            //找到比待删除节点大的最小节点,即待删除节点右子树的最小节点
            //用这个节点顶替待删除节点的位置
            Node successor = minimum(node.right);
            successor.right = removeMin(node.right);
            successor.left = node.left;
            //delete
            node.left = node.right = null;
            //return new
            return successor;
        }
    }

    public int getSize() {
        return size;
    }

    public boolean isEmpty() {
        return size == 0;
    }

    public static void main(String[] args) {
        System.out.println("Pride and Prejudice");

        ArrayList<String> words = new ArrayList<>();
        if(FileOperation.readFile("pride-and-prejudice.txt", words)) {
            System.out.println("Total words: " + words.size());

            RBTree<String, Integer> map = new RBTree<>();
            for (String word : words) {
                if (map.contains(word))
                    map.set(word, map.get(word) + 1);
                else
                    map.add(word, 1);
            }

            System.out.println("Total different words: " + map.getSize());
            System.out.println("Frequency of PRIDE: " + map.get("pride"));
            System.out.println("Frequency of PREJUDICE: " + map.get("prejudice"));
        }

        System.out.println();
    }
}
